# Assignment Details Big D Incorporated has a business opportunity to provide two different types of information to a new client. As the business analyst, you are tasked to assess the financial feasibility of this opportunity?Concepts And Terminology Of Statistics Applied To Business Decision Making

Assignment Details Big D Incorporated offers two types of information for a client. You will be the business analyst and assess this opportunity’s financial viability. Retailer looking to broaden its product ranges. The client requests Big D Incorporated’s assistance in making the right decision. Write a presentation that clarifies the differences between ordinal and nominal data. Write down 3 qualities of outdoor gear that your client would like to inquire about. Make sure that 1 of these qualitative attributes are not used. Give names to each ordinal attribute so that they can be used as a starting point for a 5-point scale. Explain the difference in interval and ratio data. Identify 2 attributes that outdoor sports goods might have in common with market research. Explain the differences between a sample and a population.
Statistics concepts and terminology – Business decision making
The Content
It is crucial to know whether data is ordinal or nominal when working with statistics. This will affect how the data is used. Nominal information simply names something without placing it in any particular order in relation to other numbers. Nominal data is illustrated by the classification of each student’s score on a test as “pass” and “fail”. (Suparji, 2021). Although nominal data provides information only limited to the simple count, it still offers knowledge about an event or group of events. For example, you can find out the number of people born in Florida each year over five years and then plot these numbers on a graph. The graph’s numbers illustrate an actual fact and not necessarily indicate a preference. These labels only give answers to the question of “how many?” There is no order nor ranking in the statistics shown on this graph. These are not real data. Ordinal data is not the same as nominal data. Oral data refers to some kind of order. Ordinal numbers can be ranked in relation to each other (Zhang and al., 2020). Consider, for example, that you are asked to rate your restaurant’s service. The service level can be rated as follows: 1 for horrible, 2 for below-average, 3 for average, 4 for good, and 5 for outstanding. The survey results are examples of ordinal data. The numbers here are given a rating, or order. For example, “4” ranks higher than “2”. Cont…

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